Information visualization systems focus on the common technical setup of a mouse, a keyboard, and a desktop display. This practice of providing visualization support only for solo desktop work ignores other exploratory phases of information work, such as preliminary sketching (on papers or whiteboards) to work out ideas and approaches to analyzing the data.
The use of paper and whiteboards among information workers is ubiquitous. Ideas, problems, and planning are oftentimes worked out initially in an informal venue. However, if the information work involves large amounts of data, it is soon necessary to make use of computational power in some tools (e.g., a spreadsheet).
Despite its familiarity and inherent benefits, the traditional whiteboard is fundamentally limited by its passive nature. All content shown must be drawn directly. For example, if charts and graphs are employed to show data, each data item must be drawn by hand. Thus, data charts on whiteboards tend to be relatively simple since drawing many data points one-by-one is tedious even for the cases where accuracy is not critical. Data-rich problem solving on a whiteboard can either be exceptionally tedious, or result in using partial or merely indicated charts and graphs.
In addition, sketched data accuracy is challenging and the quality of the plots is limited by memory; only general trends can be drawn from recollection to any real extent. Hand drawn charts are also limited in that useful functions on data are not easily estimated. Standard deviation, cardinality, and even arithmetic mean can be difficult to estimate with any accuracy, but are vital tools in the initial steps of data analysis. In other words, there is a big gap between what people think and draw on whiteboards and how people can manipulate data in the computer.